Dear R users,
A parallel implementation of the np package titled `npRmpi' is now available on CRAN. This package can take advantage of multiple core computing environments to reduce the run time associated with the methods contained in the np package.
Kindly see the vignette for details and examples on modifying np code and running it in a parallel environment. You are requested to seek local assistance for configuring machines to support MPI aware programs.
Information on the npRmpi package:
This package provides a variety of nonparametric (and semiparametric) kernel methods that seamlessly handle a mix of continuous, unordered, and ordered factor data types. This package incorporates the Rmpi package (Hao Yu <hyu at stats.uwo.ca>) with minor modifications and we are extremely grateful to Hao Yu for his contributions to the R community. We would like to gratefully acknowledge support from the Natural Sciences and Engineering Research Council of Canada (NSERC:www.nserc.ca), the Social Sciences and Humanities Research Council of Canada (SSHRC:www.sshrc.ca), and the Shared Hierarchical Academic Research Computing Network (SHARCNET:www.sharcnet.ca).
A thorough treatment of the subject matter can be found in Li, Q. and J. S. Racine (2007), Nonparametric Econometrics: Theory and Practice, Princeton University Press, ISBN: 0691121613 (768 Pages) for
those who might be interested (http://press.princeton.edu/titles/8355.html)
-- Jeffrey Racine & Tristen Hayfield.
Professor J. S. Racine Phone: (905) 525 9140 x 23825
Department of Economics FAX: (905) 521-8232
McMaster University e-mail: racinej at mcmaster.ca
1280 Main St. W.,Hamilton, URL: www.economics.mcmaster.ca/racine
Ontario, Canada. L8S 4M4
`The generation of random numbers is too important to be left to chance'